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API security scanner for automated vulnerability detection in CI/CD pipelines

API security scanner for automated vulnerability detection in CI/CD pipelines
BugDazz is an API security scanner designed to identify vulnerabilities in APIs through automated scanning. The tool integrates with CI/CD pipelines to enable real-time vulnerability detection during the development process. The scanner provides coverage for OWASP API Top 10 vulnerabilities including broken object level authorization, broken authentication, broken object property level authorization, unrestricted resource consumption, broken function level authorization, server side request forgery, security misconfiguration, improper inventory management, and unsafe consumption of APIs. It also tests for business logic vulnerabilities and other security issues beyond standard checklists. BugDazz offers authentication and access control management capabilities on a single platform. The tool generates compliance reports for standards such as PCI DSS and HIPAA. Reports can be exported in PDF, Excel, and HTML formats with detailed scan logs. The scanner includes customizable scanning templates to accelerate security testing and automate standard checks. It provides advanced user management with granular role-based permissions to control access. The platform supports Single Sign-On (SSO) for streamlined authentication. BugDazz is available as both a cloud-based solution and an on-premises deployment option. The tool is designed to handle high volumes of APIs for scalability requirements.
Common questions about SecureLayer7 BugDazz API Security Scanner including features, pricing, alternatives, and user reviews.
SecureLayer7 BugDazz API Security Scanner is API security scanner for automated vulnerability detection in CI/CD pipelines developed by SecureLayer7. It is a Application Security solution designed to help security teams with OWASP, DAST.
API security testing platform for identifying vulnerabilities in API design & runtime
API security testing platform with LLM-powered context awareness and attack simulation
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